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20202026
most citedGPUMD: A package for constructing accurate machine-learned potentials and performing highly efficient atomistic simulations

463 citations · 787 across the 17 of their papers we have counts for

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cond-mat.mtrl-sci2023★ 203 cited

General-purpose machine-learned potential for 16 elemental metals and their alloys

Keke Song, Rui Zhao, Jiahui Liu +25

Machine-learned potentials (MLPs) have exhibited remarkable accuracy, yet the lack of general-purpose MLPs for a broad spectrum of elements and their alloys limits their applicabil…